Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Exploratory Data Analysis 145

Alation

FEBRUARY 1, 2022

Most organizations depend on institutional knowledge to populate data catalogs; without any form of automation, these leaders are forced to interview numerous people to find out who is the SME for a particular data set and have that person populate the catalog. Data lakes are repositories where much of this data winds up.

Data Lakes 52

Data Lakes Data Governance ML ML 52

Tableau

APRIL 18, 2022

Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Provide a visual and direct way to combine, shape, and clean data in a few clicks. Ensure the behaves the way you want it to— especially sensitive data and access.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Provide a visual and direct way to combine, shape, and clean data in a few clicks. Ensure the behaves the way you want it to— especially sensitive data and access.

Tableau 98

Tableau Data Quality Analytics Analytics 98

Pickl AI

JULY 25, 2024

Data Ingestion Meaning At its core, It refers to the act of absorbing data from multiple sources and transporting it to a destination, such as a database, data warehouse, or data lake. Batch Processing In this method, data is collected over a period and then processed in groups or batches.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

Pickl AI

OCTOBER 6, 2024

It can occur in bulk, where large batches of data are uploaded at once, or incrementally, where data is loaded continuously or at scheduled intervals. A successful load ensures Analysts and decision-makers access to up-to-date, clean data. These tools are vital in ensuring efficiency and accuracy in the ETL workflow.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

Snorkel AI

JULY 12, 2024

This approach can be particularly effective when dealing with real-world applications where data is often noisy or imbalanced. Model-centric AI is well suited for scenarios where you are delivered clean data that has been perfectly labeled. Raw Data: MinIO is the best solution for collecting and storing raw unstructured data.

AI 52

AI AI Data Lakes Artificial Intelligence 52